Instructions to use tiya1012/crossde_electra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiya1012/crossde_electra with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tiya1012/crossde_electra")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tiya1012/crossde_electra") model = AutoModelForSequenceClassification.from_pretrained("tiya1012/crossde_electra", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from tiya1012/crossde_electra: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
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https://huggingface.co/tiya1012/crossde_electra/resolve/main/tokenizer.json
- Command line
-
hf download hf://tiya1012/crossde_electra/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/tiya1012/crossde_electra/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.